Bacterial Identification and Drug Susceptibility Patterns in Pregnant and Non Pregnant UTI Patients

Bacterial Identification and Drug Susceptibility Patterns in Pregnant and Non Pregnant UTI Patients by Syeda Sograh Fatima, Eman Al Mussaed.

This book provides a review of essential research on urinary tract infections (UTIs), as well as a broader perspective on methodologies adopted for the isolation and identification of the bacteria from urine samples of pregnant and non-pregnant women on the basis of their cultural, morphological and...

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Bibliographic Details
Main Authors: Fatima, Syeda Sograh (Author), Mussaed, Eman Al (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Series:SpringerBriefs in Forensic and Medical Bioinformatics,
Springer eBook Collection.
Subjects:
Biomedical engineering.
Health informatics.
Bioinformatics.
Bacteriology.
Signal processing.
Image processing.
Speech processing systems.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Description
Summary:This book provides a review of essential research on urinary tract infections (UTIs), as well as a broader perspective on methodologies adopted for the isolation and identification of the bacteria from urine samples of pregnant and non-pregnant women on the basis of their cultural, morphological and biochemical characteristics. The identification is extended to the strain level by means of molecular identification involving BLAST as a bioinformatics tool. The book also addresses the roles of various other bioinformatics tools for tracing the phylogenetic tree and conservation studies among the bacteriocin of the identified bacteria. Lastly, it assesses the antibiotics resistance patterns of these isolates.
Physical Description:VI, 78 p. 37 illus., 36 illus. in color. online resource.
ISBN:9789811047503
ISSN:2196-8845
DOI:10.1007/978-981-10-4750-3

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